R2F: A general retrieval, reading and fusion framework for document-level natural language inference

R2F: A general retrieval, reading and fusion framework for document-level natural language inference

Document-level natural language inference (DocNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents. Current datasets and baselines largely follow sentence-level settings, but fail to address th...

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Bibliographic Details
Main Authors: WANG, Hao, CAO, Yixin, LI, Yangguang, HUANG, Zhen, WANG, Kun, SHAO, Jing
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
Natural language processing systems
Language processing
Interpretability
Databases and Information Systems
Programming Languages and Compilers
Online Access:https://ink.library.smu.edu.sg/sis_research/7481
https://ink.library.smu.edu.sg/context/sis_research/article/8484/viewcontent/docnli_emnlp2022.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/7481
https://ink.library.smu.edu.sg/context/sis_research/article/8484/viewcontent/docnli_emnlp2022.pdf

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